Delay analysis of a probabilistic priority discipline

In high speed networks, the strict priority (SP) scheduling discipline is perhaps the most common and simplest method to schedule packets from different classes of applications, each with diverse performance requirements. With this discipline, however, packets at higher priority levels can starve packets at lower priority levels. To resolve this starvation problem, we propose to assign a parameter to each priority queue in the SP discipline. The assigned parameter determines the probability with which its corresponding queue is served when the queue is polled by the server. We thus form a new packet scheduling discipline, referred to as the probabilistic priority (PP) discipline. By properly setting the assigned parameters, service differentiation as well as fairness among traffic classes can be achieved in PP. In addition, the PP discipline can be easily reduced to the ordinary SP discipline or to the reverse SP discipline.

Achieving differentiated services through multi-class probabilistic priority scheduling

The paper proposes two IP packet aggregation techniques, called DAT (Deterministic Aggregation Technique) and WATT (Work-conserving Aggregation Technique with Timer), to adapt IP traffic to a multi-service optical slotted network. To perform aggregation, IP packets belonging to different classes of service (CoS) are polled according to the strict priority (SP) or to an hybrid version of the probabilistic priority (PP) scheduling discipline originally proposed in [1, 2]. An approximate analytical model is given in the case of DAT under the SP discipline. In addition, extensive simulations are used to study the impact of self-similar traffic on the aggregation processes. Finally, performance comparisons between the aggregation techniques and the standard approach (where no aggregation is performed) are carried out in the context of a slotted dual bus optical ring network (SDBORN) which is a candidate viable solution for metropolitan area networks (MAN).

In March of 2020, elective surgical procedures in New York State were suspended in response to the COVID-19 pandemic. At Northwell Health, this lasted a total of 8 weeks, leaving plastic surgeons responsible for recording and rescheduling delayed procedures. Many plastic and reconstructive procedures are considered elective, but these procedures can be time sensitive, and delays can have a negative impact on patient care.1 Our goal was to compare the rates of completion and time to completion between different priority groups and procedure types in order to predict potential consequences for one's practice if future suspensions in elective surgery were to occur. We hypothesized that procedures grouped in the reconstructive categories with higher priority levels would have a higher completion rate and lower time to completion compared to less urgent, aesthetic based procedures. Plastic surgeons working for our department were responsible for keeping track of their suspended cases between March 23, 2020, and May 19, 2020.2,3 Under the discretion of the attending plastic surgeon, cases were categorized into procedure type, priority level, and surgery setting. The procedure types included aesthetic, pediatrics/craniofacial, hand, general, and reconstructive. The priority classes were elective, nonurgent, semiurgent, urgent, and emergent. The surgery setting was classified into inpatient and outpatient. In total, we examined 135 surgical cases that were suspended (Table 1). The average patient age was 45.8 years, and 45.9 percent of the surgical procedures were completed by the end of August of 2020, more than 3 months after the suspension was lifted. Of those that were completed, the average time to completion from the original surgical date was 79.2 days. Surgery classifications are summarized in Table 1. We ran binary logistic regressions that showed no significant correlation between the surgery type, urgency, or priority class and whether or not the surgery was completed. In addition, linear regression analyses did not show a significant correlation between the surgery type, urgency, or priority class and the time it took to complete the surgery. All the models controlled for patient age and whether or not there was malignancy. Table 1. - Summary of Sample by Procedure Priority Procedure Classification No. of Patients Percent of Sample Priority Elective 8 5.93% Nonurgent 80 52.29% Semiurgent 22 16.30% Urgent 24 17.78% Emergent 1 0.01% Type Aesthetic 12 8.89% Pediatrics/craniofacial 10 7.41% Hand 9 6.67% General 35 25.93% Reconstructive 68 50.37% No type specified 1 0.74% Location Inpatient 34 25.19% Outpatient 66 48.89% No location specified 35 25.93% Our surprising results may be due to several factors, including differences in patients' concerns with undergoing surgery during a pandemic, patients' continuous desire to undergo aesthetic surgery, or a lack of prioritization of urgent cases when rescheduling surgery. With new variants of SARS-CoV-2 emerging and the number of COVID-19 cases climbing rapidly in the United States,5 plastic surgeons must be prepared for another potential suspension of surgery.6 Plastic surgery departments and private practices can use our experience to guide their recovery from future surgical suspension. Prior studies have already shown the tremendous economic impact of surgery delays on plastic surgeons.4Additional research is needed, however, to evaluate the impact of delays on patient care and quality of life. A more systematic approach to rescheduling surgery, which prioritizes the most vulnerable patients, is needed. DISCLOSURE The authors have no relevant financial disclosures to report.

ATM switches are now being designed to allow connections to be partitioned into priority classes, with packets being emitted for higher priority classes before packets are emitted for lower priority classes. Accordingly, allocation of network resources based on different priority levels is becoming a realistic possibility. Thus, we need new methods for connection admission control and capacity planning that take account of the priority structure. We show that the notion of effective bandwidths can be used for these purposes when appropriately extended. The key is to have admissibility of a set of connections determined by a linear constraint for each priority level, involving a performance criterion for each priority level. For this purpose, connections are assigned more than one effective bandwidth, one for its own priority level and one for each lower priority level. Candidate effective bandwidths for each priority level can be determined by using previous methods associated with the first-in first-out discipline. The proposed effective bandwidth structure makes it possible to apply product-form stochastic loss network models to perform dimensioning.

Optical MAN ring performance with traffic aggregations

We study a two-stage priority service system in which the first stage can be interrupted but the second stage can not. There are two classes of customers, low priority and high priority. The server adopts the preemptive priority discipline if the service is at the first stage and adopts the non-preemptive priority discipline if it is at the second stage service. By treating the high priority queue as bounded, the steady-state probability vector for the system can be expressed in a matrix-geometric form. We also obtain the sojourn time of an arbitrary low priority customer. The numerical results demonstrate the effectiveness of our approach.

Problem Statement: Improper triage and prioritization of big-data patients may result in erroneous strategic decisions. An example of such wrong decision making includes the triage of patients with chronic heart disease to low-priority groups. Incorrect decisions may jeopardize the patients’ health.Objective: This study aims to evaluate and score the big data of patients with chronic heart disease and of those who require urgent attention. The assessment is based on multicriteria decision making in a telemedical environment to improve the triage and prioritization processes.Methods: A hands-on study was performed. A total of 500 patients with chronic heart disease manifested in different symptoms and under various emergency levels were evaluated on the basis of the following four main measures. An electrocardiogram sensor was used to measure the electrical signals of the contractile activity of the heart over time. A SpO2sensor was employed to determine the blood oxygen saturation levels of the patients. A blood pressure sensor was used to obtain the physiological data of the systolic and diastolic blood pressures of the patients. Finally, a non-sensory measurement (text frame) was conducted to assess chest pain and breathing. The patients were prioritized on the basis of a set of measurements by utilizing integrated back-forward adjustment for weight computation and technique for order performance by similarity to ideal solution.Discussion Results: Patients with the most urgent cases were given the highest priority level, whereas those with the least urgent cases were assigned with the lowest priority level among all patients’ scores. The first three patients assigned to the medical committee of doctors were proven to be the most critical emergency cases with the highest priority level on the basis of their clinical symptoms. By contrast, the last three patients were proven to be the least critical emergency cases and given the lowest priority levels relative to other patients. The throughput measurement in terms of scalability based on our proposed algorithm was more efficient than that of the benchmark algorithm. Finally, the new method for determining the “big data” patients characteristics based on “4Vs” was suggested.

Polynomial goal programming: A procedure for modeling preference trade-offs

We consider an inventory system under continuous review with two demand classes that are different in terms of service level required (or penalty cost incurred for backordering of demand). Prior literature has proposed the critical level rationing (CLR) policy under which the demand from the lower priority class is backordered once inventory falls below the critical level. While this reduces the penalty cost for the higher demand class, the fill rate achieved for the lower priority demand class gets compromised. In this study, we propose a new class of two‐bin (2B) policy for the problem. The proposed 2B policy assigns separate bins of inventory for the two demand classes. The demand for each class is fulfilled from its assigned bin. However, when the bin intended for the higher demand class is empty, the demand from the higher class can still be fulfilled with the inventory from the other bin. The advantage of the 2B policy is that better fill rates are achieved, especially for the lower demand class. Computational results show that the proposed policy is able to provide a much higher service level for the lower priority class demand without increasing the total cost too much and without affecting the service level for the higher priority class. When a service level constrained optimization problem is considered, the 2B policy dominates the CLR policy when the service level difference for the two classes is not too high or the service levels required for both the classes are relatively lower.

This paper studies the design and performance of the Probabilistic Priority (PP) packet scheduling algorithm to schedule packets. Unlike an earlier design that uses fractional arithmetic and prohibits large number of classes, we present an integer PP algorithm and show that PP is a special scheme of applying lottery scheduling to bandwidth allocation in a strict priority sense. We then propose a Multi-winner PP (MPP) scheduler using multi-winner lottery scheduling to improve the throughput and response time accuracy and a flexible ticket transfer algorithm to improve the deadline violation probability in probabilistic scheduling. Finally, we investigate the issue of parameter assignment for an MPP scheduler and use our techniques to implement a prototype Assured Forwarding (AF) mechanism in a network processor.

A significant amount of recent research has been focused on the stability of multiclass open networks of queues (MONQs). It has been shown that these networks may be unstable under various queueing disciplines even when at each one of the nodes the arrival rate is less than the service rate. Clearly, in such cases the expected delay and the expected number of customers in the system are infinite. In this paper we propose a new class of scheduling rules that can be used in multiclass queueing networks. We refer to this class as the stable shortfall-based priority (SSBP) rules. This SSBP class itself belongs to a larger class of rules, which we refer to as the shortfall-based priority (SBP) rules. SBP is a generalization of the standard non-preemptive priority rule in which customers of the same priority class are served first-come, first-served (FCFS). Rules from SBP can mimic FCFS as well as the so-called strict or head-of-the-line priority disciplines. We show that the use of any rule from the SSBP class ensures stability in a broad class of MONQs found in practice. We proceed with the construction of a sample path inequality for the work done by an SSBP server and show how this inequality can be used to derive upper bounds for the delay when service times are bounded. Bounds for the expected delay of each class of customers in an MONQ are then obtained under the assumptions that the external arrival processes have i.i.d. interarrival times, the routings are deterministic and the service times at each step of the route are bounded. In order to derive these bounds for the average delay in an MONQ we make use of some of the classical ideas of Kingman.

The IEEE 802.6 standard for Metropolitan Area Networks does not provide multiple priority traffic for connectionless data services. A priority mechanism that was considered for the standard showed to be not effective. As of now, there exists no protocol for multiple access dual bus networks that is able to implement pre-emptive priorites and, at the same time, can satisfy minimal fairness requirements for transmissions at the highest priority level. In this study, a protocol with strictly pre-emptive priorities, i.e., a protocol that does not admit low priority traffic if the load from high priority traffic exceeds the capacity of the transmission channel, is presented. The protocol is derived from a unique bandwidth allocation scheme with a full utilization of the bus capacity, with a fair distribution of bandwidth respective to traffic from a particular priority level and with pre-emptive priorities. The performance of the presented protocol is compared to a priority mechanism that is based on the bandwidth balancing mechanism. It is shown that adopting the new protocol results in shorter access delays for high priority transmissions.

IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. However, the long handoff latency of the standard handoff scheme for IEEE 802.11 has become an important issue for seamless roaming in vehicular environments, as more handoffs may be triggered due to the higher mobility of vehicles. This thesis presents a new and fast location-based handoff scheme particularly designed for vehicular environments. With the position and movement direction of a vehicle and the locations of the surrounding APs, our protocol is able to accurately predict several possible APs that the vehicle may visit in the future and to assign these APs different priority levels. APs on higher priority levels will be first scanned. Once a response to scanning from an AP is received, the scanning process ends immediately. A blacklist scheme is also used to exclude those APs that showed no response to the scanning during previous handoffs. Thus, time spent on scanning APs is supposed to be significantly reduced. The simulation results show that the proposed scheme attains not only a lower prediction error rate, but also a lower MAC layer handoff latency, and that it has a smaller influence on jitter and throughput; moreover, these results show that the proposed scheme has a smaller total number of handoffs than other handoff schemes.

This paper discuss on how to develop a hard real-time machine control system with Microsoft Windows NT Operating System, where the respond must be within 0.5 milliseconds. The attempt to use a general-purpose operating system (Microsoft Windows NT 4.0 Workstation) is because there is abundance of Commercial-Off-the-Shelf Components (COTS), easily available tools (compilers, and 3 party tools) and need not to learn another operating system behavior. The most important factor is there is no single dominant operating system or tools vendor for real-time operating system. Since the no single dominant real-time operating system development under real-time operating system is riskier and more costly. Ideally codes must be portable between different operating system where it is apparent with Windows platforms, Windows 95/98, Windows ME, Windows 2000, Windows XP or even Windows CE. Firstly study was done on how Microsoft Windows NT operating system works internally from materials from Microsoft Software Development Network (MSDN). Secondly study was done how to take advantage of the operating system to create a real time application. Microsoft Windows NT is a general purpose operating system that does not support real time application development, but it has all the vital elements that a real time operating system needs. The vital elements are priority-driven, preemptive scheduler, preemptive interrupt handler (for critical interrupts), deferred procedure calls (DPC) for non-critical (DPC executes after ISR), synchronization and deterministic response time. With these vital elements and some modification to application codes to enable it to execute in higher priority level, would result a real time application. This does not mean changing all the codes to higher priority is the solution, as it would cause system to malfunction as other device driver or low-level interface run at high priority too and this would lock up the system. With the combination of priority level, synchronization a complete real time solution can be implemented and this paper covers the concept. This concept also explains what was done to overcome the need of special hardware (as recommended) to accomplish hard real-time application with the response of 0.5 milliseconds.